{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Best Practices for Preprocessing Natural Language Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, we improve the quality of our Project Gutenberg word vectors by adopting best-practices for preprocessing natural language data.\n",
    "\n",
    "**N.B.:** Some, all or none of these preprocessing steps may be helpful to a given downstream application. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load dependencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# the initial block is copied from creating_word_vectors_with_word2vec.ipynb\n",
    "import nltk\n",
    "from nltk import word_tokenize, sent_tokenize\n",
    "import gensim\n",
    "from gensim.models.word2vec import Word2Vec\n",
    "from sklearn.manifold import TSNE\n",
    "import pandas as pd\n",
    "from bokeh.io import output_notebook, output_file\n",
    "from bokeh.plotting import show, figure\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to /home/jovyan/nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('punkt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# new!\n",
    "import string\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem.porter import *\n",
    "from gensim.models.phrases import Phraser, Phrases\n",
    "from keras.preprocessing.text import one_hot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to /home/jovyan/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package gutenberg to /home/jovyan/nltk_data...\n",
      "[nltk_data]   Package gutenberg is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nltk.download('gutenberg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from nltk.corpus import gutenberg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gberg_sents = gutenberg.sents()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Iteratively preprocess a sentence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### a tokenized sentence: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['She',\n",
       " 'was',\n",
       " 'the',\n",
       " 'youngest',\n",
       " 'of',\n",
       " 'the',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'of',\n",
       " 'a',\n",
       " 'most',\n",
       " 'affectionate',\n",
       " ',',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " ';',\n",
       " 'and',\n",
       " 'had',\n",
       " ',',\n",
       " 'in',\n",
       " 'consequence',\n",
       " 'of',\n",
       " 'her',\n",
       " 'sister',\n",
       " \"'\",\n",
       " 's',\n",
       " 'marriage',\n",
       " ',',\n",
       " 'been',\n",
       " 'mistress',\n",
       " 'of',\n",
       " 'his',\n",
       " 'house',\n",
       " 'from',\n",
       " 'a',\n",
       " 'very',\n",
       " 'early',\n",
       " 'period',\n",
       " '.']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gberg_sents[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### to lowercase: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'was',\n",
       " 'the',\n",
       " 'youngest',\n",
       " 'of',\n",
       " 'the',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'of',\n",
       " 'a',\n",
       " 'most',\n",
       " 'affectionate',\n",
       " ',',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " ';',\n",
       " 'and',\n",
       " 'had',\n",
       " ',',\n",
       " 'in',\n",
       " 'consequence',\n",
       " 'of',\n",
       " 'her',\n",
       " 'sister',\n",
       " \"'\",\n",
       " 's',\n",
       " 'marriage',\n",
       " ',',\n",
       " 'been',\n",
       " 'mistress',\n",
       " 'of',\n",
       " 'his',\n",
       " 'house',\n",
       " 'from',\n",
       " 'a',\n",
       " 'very',\n",
       " 'early',\n",
       " 'period',\n",
       " '.']"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[w.lower() for w in gberg_sents[4]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### remove stopwords and punctuation: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stpwrds = stopwords.words('english') + list(string.punctuation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['i',\n",
       " 'me',\n",
       " 'my',\n",
       " 'myself',\n",
       " 'we',\n",
       " 'our',\n",
       " 'ours',\n",
       " 'ourselves',\n",
       " 'you',\n",
       " 'your',\n",
       " 'yours',\n",
       " 'yourself',\n",
       " 'yourselves',\n",
       " 'he',\n",
       " 'him',\n",
       " 'his',\n",
       " 'himself',\n",
       " 'she',\n",
       " 'her',\n",
       " 'hers',\n",
       " 'herself',\n",
       " 'it',\n",
       " 'its',\n",
       " 'itself',\n",
       " 'they',\n",
       " 'them',\n",
       " 'their',\n",
       " 'theirs',\n",
       " 'themselves',\n",
       " 'what',\n",
       " 'which',\n",
       " 'who',\n",
       " 'whom',\n",
       " 'this',\n",
       " 'that',\n",
       " 'these',\n",
       " 'those',\n",
       " 'am',\n",
       " 'is',\n",
       " 'are',\n",
       " 'was',\n",
       " 'were',\n",
       " 'be',\n",
       " 'been',\n",
       " 'being',\n",
       " 'have',\n",
       " 'has',\n",
       " 'had',\n",
       " 'having',\n",
       " 'do',\n",
       " 'does',\n",
       " 'did',\n",
       " 'doing',\n",
       " 'a',\n",
       " 'an',\n",
       " 'the',\n",
       " 'and',\n",
       " 'but',\n",
       " 'if',\n",
       " 'or',\n",
       " 'because',\n",
       " 'as',\n",
       " 'until',\n",
       " 'while',\n",
       " 'of',\n",
       " 'at',\n",
       " 'by',\n",
       " 'for',\n",
       " 'with',\n",
       " 'about',\n",
       " 'against',\n",
       " 'between',\n",
       " 'into',\n",
       " 'through',\n",
       " 'during',\n",
       " 'before',\n",
       " 'after',\n",
       " 'above',\n",
       " 'below',\n",
       " 'to',\n",
       " 'from',\n",
       " 'up',\n",
       " 'down',\n",
       " 'in',\n",
       " 'out',\n",
       " 'on',\n",
       " 'off',\n",
       " 'over',\n",
       " 'under',\n",
       " 'again',\n",
       " 'further',\n",
       " 'then',\n",
       " 'once',\n",
       " 'here',\n",
       " 'there',\n",
       " 'when',\n",
       " 'where',\n",
       " 'why',\n",
       " 'how',\n",
       " 'all',\n",
       " 'any',\n",
       " 'both',\n",
       " 'each',\n",
       " 'few',\n",
       " 'more',\n",
       " 'most',\n",
       " 'other',\n",
       " 'some',\n",
       " 'such',\n",
       " 'no',\n",
       " 'nor',\n",
       " 'not',\n",
       " 'only',\n",
       " 'own',\n",
       " 'same',\n",
       " 'so',\n",
       " 'than',\n",
       " 'too',\n",
       " 'very',\n",
       " 's',\n",
       " 't',\n",
       " 'can',\n",
       " 'will',\n",
       " 'just',\n",
       " 'don',\n",
       " 'should',\n",
       " 'now',\n",
       " 'd',\n",
       " 'll',\n",
       " 'm',\n",
       " 'o',\n",
       " 're',\n",
       " 've',\n",
       " 'y',\n",
       " 'ain',\n",
       " 'aren',\n",
       " 'couldn',\n",
       " 'didn',\n",
       " 'doesn',\n",
       " 'hadn',\n",
       " 'hasn',\n",
       " 'haven',\n",
       " 'isn',\n",
       " 'ma',\n",
       " 'mightn',\n",
       " 'mustn',\n",
       " 'needn',\n",
       " 'shan',\n",
       " 'shouldn',\n",
       " 'wasn',\n",
       " 'weren',\n",
       " 'won',\n",
       " 'wouldn',\n",
       " '!',\n",
       " '\"',\n",
       " '#',\n",
       " '$',\n",
       " '%',\n",
       " '&',\n",
       " \"'\",\n",
       " '(',\n",
       " ')',\n",
       " '*',\n",
       " '+',\n",
       " ',',\n",
       " '-',\n",
       " '.',\n",
       " '/',\n",
       " ':',\n",
       " ';',\n",
       " '<',\n",
       " '=',\n",
       " '>',\n",
       " '?',\n",
       " '@',\n",
       " '[',\n",
       " '\\\\',\n",
       " ']',\n",
       " '^',\n",
       " '_',\n",
       " '`',\n",
       " '{',\n",
       " '|',\n",
       " '}',\n",
       " '~']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stpwrds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'youngest',\n",
       " 'two',\n",
       " 'daughters',\n",
       " 'affectionate',\n",
       " 'indulgent',\n",
       " 'father',\n",
       " 'consequence',\n",
       " 'sister',\n",
       " 'marriage',\n",
       " 'mistress',\n",
       " 'house',\n",
       " 'early',\n",
       " 'period']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[w.lower() for w in gberg_sents[4] if w not in stpwrds]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### stem words: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stemmer = PorterStemmer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['she',\n",
       " 'youngest',\n",
       " 'two',\n",
       " 'daughter',\n",
       " 'affection',\n",
       " 'indulg',\n",
       " 'father',\n",
       " 'consequ',\n",
       " 'sister',\n",
       " 'marriag',\n",
       " 'mistress',\n",
       " 'hous',\n",
       " 'earli',\n",
       " 'period']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[stemmer.stem(w.lower()) for w in gberg_sents[4] if w not in stpwrds]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### handle bigram collocations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "phrases = Phrases(gberg_sents) # train detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "bigram = Phraser(phrases) # create a more efficient Phraser object for transforming sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'two', b'daughters'): (19, 11.966813731181546),\n",
       " (b'her', b'sister'): (195, 17.7960829227865),\n",
       " (b\"'\", b's'): (9781, 31.066242737744524),\n",
       " (b'very', b'early'): (24, 11.01214147275924),\n",
       " (b'Her', b'mother'): (14, 13.529425062715127),\n",
       " (b'long', b'ago'): (38, 63.22343628984788),\n",
       " (b'more', b'than'): (541, 29.023584433996874),\n",
       " (b'had', b'been'): (1256, 22.306024648925288),\n",
       " (b'an', b'excellent'): (54, 39.063874851750626),\n",
       " (b'Miss', b'Taylor'): (48, 453.75918026073305),\n",
       " (b'very', b'fond'): (28, 24.134280468850747),\n",
       " (b'passed', b'away'): (25, 12.35053642325912),\n",
       " (b'too', b'much'): (173, 31.376002029426687),\n",
       " (b'did', b'not'): (935, 11.728416217142811),\n",
       " (b'any', b'means'): (27, 14.096964108090186),\n",
       " (b'wedding', b'-'): (15, 17.4695197740113),\n",
       " (b'Her', b'father'): (18, 13.129571562488772),\n",
       " (b'after', b'dinner'): (21, 21.5285481168817),\n",
       " (b'self', b'-'): (124, 47.79018053120332),\n",
       " (b'sixteen', b'years'): (12, 107.0461671612265),\n",
       " (b'five', b'years'): (42, 40.128755673408115),\n",
       " (b'years', b'old'): (176, 54.735425236061104),\n",
       " (b'seven', b'years'): (51, 52.59411150244507),\n",
       " (b'each', b'other'): (236, 79.4168405322873),\n",
       " (b'a', b'mile'): (48, 12.783091600264584),\n",
       " (b'must', b'be'): (601, 10.229989650632808),\n",
       " (b'difference', b'between'): (44, 220.5253730524468),\n",
       " (b'could', b'not'): (1049, 10.870983286982371),\n",
       " (b'having', b'been'): (49, 11.538018331569376),\n",
       " (b'miles', b'off'): (16, 34.7868137375225),\n",
       " (b'at', b'Hartfield'): (66, 27.282227059708397),\n",
       " (b'her', b'husband'): (158, 27.544395195049724),\n",
       " (b'in', b'spite'): (96, 13.441914963088442),\n",
       " (b'Emma', b'could'): (61, 11.335111257744053),\n",
       " (b'every', b'body'): (127, 36.972582976825784),\n",
       " (b'no', b'means'): (80, 32.57361823161739),\n",
       " (b'his', b'own'): (773, 10.402387689390995),\n",
       " (b'obliged', b'to'): (179, 10.43662879984823),\n",
       " (b'able', b'to'): (348, 11.446828804673226),\n",
       " (b'very', b'much'): (234, 16.21027499400206),\n",
       " (b'have', b'been'): (986, 17.981191047801964),\n",
       " (b'great', b'deal'): (181, 118.04013764577145),\n",
       " (b'\"', b'Poor'): (30, 10.125586409383336),\n",
       " (b'agree', b'with'): (25, 13.611743912451109),\n",
       " (b'-', b'humoured'): (22, 33.94078127522195),\n",
       " (b'for', b'ever'): (555, 12.4761138144463),\n",
       " (b'This', b'is'): (353, 11.381028160111825),\n",
       " (b'three', b'times'): (36, 35.42578086743132),\n",
       " (b'my', b'dear'): (253, 24.47894249615343),\n",
       " (b'How', b'often'): (12, 12.377968718725876),\n",
       " (b'My', b'dear'): (85, 84.80698289930197),\n",
       " (b'so', b'far'): (98, 10.161632478973766),\n",
       " (b'\"', b'No'): (351, 15.063706270011586),\n",
       " (b'We', b'must'): (68, 18.765646900386386),\n",
       " (b'last', b'night'): (63, 23.592598950882213),\n",
       " (b'doubt', b'whether'): (12, 22.924130736398396),\n",
       " (b'anywhere', b'else'): (6, 16.100101533414907),\n",
       " (b'I', b'am'): (2428, 16.951297329049222),\n",
       " (b'very', b'glad'): (46, 18.28434074650975),\n",
       " (b'am', b'sure'): (282, 65.1446020744797),\n",
       " (b'very', b'pretty'): (39, 20.068178868120455),\n",
       " (b'be', b'able'): (121, 11.347612277348256),\n",
       " (b'immediately', b'afterwards'): (10, 41.06053966483414),\n",
       " (b'sensible', b'man'): (17, 14.541388094211703),\n",
       " (b'intimate', b'friend'): (6, 21.898760623229464),\n",
       " (b'connected', b'with'): (31, 18.375854281808998),\n",
       " (b'than', b'usual'): (30, 28.951968704471486),\n",
       " (b'Brunswick', b'Square'): (11, 10881.307917888562),\n",
       " (b'some', b'time'): (146, 12.926553753557874),\n",
       " (b'poor', b'Isabella'): (10, 41.30241100647832),\n",
       " (b'It', b'is'): (777, 11.705870174225897),\n",
       " (b'am', b'afraid'): (65, 25.627391867391864),\n",
       " (b'moonlight', b'night'): (6, 14.745374344301382),\n",
       " (b'Look', b'at'): (33, 13.630464729284446),\n",
       " (b'\"', b'Well'): (311, 21.191330893669),\n",
       " (b'vast', b'deal'): (11, 61.90400400400401),\n",
       " (b'an', b'hour'): (150, 41.75757187695002),\n",
       " (b'pretty', b'well'): (20, 17.716415202444615),\n",
       " (b'tolerably', b'well'): (7, 18.357580705009276),\n",
       " (b'\"', b'Ah'): (83, 17.279509006244886),\n",
       " (b'Ah', b'!'): (68, 37.53295698121932),\n",
       " (b\"'\", b'Tis'): (64, 23.239343942788935),\n",
       " (b'Miss', b'Woodhouse'): (173, 294.52709701744294),\n",
       " (b'you', b'please'): (93, 13.035980721875688),\n",
       " (b'any', b'rate'): (47, 83.92034351736973),\n",
       " (b',\"', b'said'): (2583, 36.03254133384804),\n",
       " (b'My', b'dearest'): (7, 26.665272507761294),\n",
       " (b'so', b'much'): (483, 20.56443776042493),\n",
       " (b'much', b'less'): (38, 19.104435569934505),\n",
       " (b'any', b'body'): (93, 21.716438732250484),\n",
       " (b'has', b'been'): (263, 29.2606767165493),\n",
       " (b'been', b'used'): (29, 14.09410182779525),\n",
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       " (b'almost', b'entirely'): (13, 36.10558657179347),\n",
       " (b'lower', b'part'): (8, 15.927465187754331),\n",
       " (b'staring', b'at'): (33, 25.04597894006017),\n",
       " (b'an', b'oath'): (37, 44.98731955716202),\n",
       " (b'wiser', b'than'): (8, 29.373088249263795),\n",
       " (b'prejudice', b'against'): (7, 39.177763699714916),\n",
       " (b'both', b'sides'): (30, 99.67073029216844),\n",
       " (b'my', b'soul'): (234, 16.443509373671976),\n",
       " (b'rejoice', b'over'): (13, 10.116903194143386),\n",
       " (b'same', b'instant'): (19, 25.162444780283654),\n",
       " (b'every', b'one'): (375, 14.671392435905247),\n",
       " (b'their', b'seats'): (11, 12.658554059033037),\n",
       " (b'their', b'mouths'): (24, 26.497142818484406),\n",
       " (b'short', b'silence'): (9, 19.427041120849434),\n",
       " (b'-', b'blooded'): (7, 17.4695197740113),\n",
       " (b'general', b'character'): (6, 10.833526031812768),\n",
       " (b'fifty', b'pounds'): (6, 35.380799816923165),\n",
       " (b'be', b'saved'): (61, 13.4097233300756),\n",
       " (b'threw', b'himself'): (8, 10.02991247371238),\n",
       " (b'some', b'moments'): (13, 21.006148097826088),\n",
       " (b'exclaimed', b'Mrs'): (11, 12.149128235351897),\n",
       " (b'compassion', b'on'): (20, 13.01248600742343),\n",
       " (b'an', b'explanation'): (12, 16.343049682875264),\n",
       " (b'our', b'hearts'): (17, 14.94420279348509),\n",
       " (b'minutes', b'afterwards'): (7, 22.216989096657148),\n",
       " (b'make', b'haste'): (26, 50.3846341860844),\n",
       " (b\"'\", b'n'): (26, 22.533063472289214),\n",
       " (b'n', b\"'\"): (20, 16.09504533734944),\n",
       " (b'rising', b'sun'): (7, 13.06573846170098),\n",
       " (b'-', b'faced'): (30, 42.60858481466171),\n",
       " (b'an', b'atonement'): (66, 89.61132859823739),\n",
       " (b'atonement', b'for'): (64, 24.315805643301744),\n",
       " (b'\"', b'Look'): (42, 10.09252327008739),\n",
       " (b'Look', b'here'): (14, 26.311681865240885),\n",
       " ...}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigram.phrasegrams # output count and score of each bigram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Jon', 'lives', 'in', 'New', 'York', 'City']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"Jon lives in New York City\".split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Jon', 'lives', 'in', 'New_York', 'City']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bigram[\"Jon lives in New York City\".split()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preprocess the corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lower_sents = []\n",
    "for s in gberg_sents:\n",
    "    lower_sents.append([w.lower() for w in s if w not in list(string.punctuation)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['emma', 'by', 'jane', 'austen', '1816'],\n",
       " ['volume', 'i'],\n",
       " ['chapter', 'i'],\n",
       " ['emma',\n",
       "  'woodhouse',\n",
       "  'handsome',\n",
       "  'clever',\n",
       "  'and',\n",
       "  'rich',\n",
       "  'with',\n",
       "  'a',\n",
       "  'comfortable',\n",
       "  'home',\n",
       "  'and',\n",
       "  'happy',\n",
       "  'disposition',\n",
       "  'seemed',\n",
       "  'to',\n",
       "  'unite',\n",
       "  'some',\n",
       "  'of',\n",
       "  'the',\n",
       "  'best',\n",
       "  'blessings',\n",
       "  'of',\n",
       "  'existence',\n",
       "  'and',\n",
       "  'had',\n",
       "  'lived',\n",
       "  'nearly',\n",
       "  'twenty',\n",
       "  'one',\n",
       "  'years',\n",
       "  'in',\n",
       "  'the',\n",
       "  'world',\n",
       "  'with',\n",
       "  'very',\n",
       "  'little',\n",
       "  'to',\n",
       "  'distress',\n",
       "  'or',\n",
       "  'vex',\n",
       "  'her'],\n",
       " ['she',\n",
       "  'was',\n",
       "  'the',\n",
       "  'youngest',\n",
       "  'of',\n",
       "  'the',\n",
       "  'two',\n",
       "  'daughters',\n",
       "  'of',\n",
       "  'a',\n",
       "  'most',\n",
       "  'affectionate',\n",
       "  'indulgent',\n",
       "  'father',\n",
       "  'and',\n",
       "  'had',\n",
       "  'in',\n",
       "  'consequence',\n",
       "  'of',\n",
       "  'her',\n",
       "  'sister',\n",
       "  's',\n",
       "  'marriage',\n",
       "  'been',\n",
       "  'mistress',\n",
       "  'of',\n",
       "  'his',\n",
       "  'house',\n",
       "  'from',\n",
       "  'a',\n",
       "  'very',\n",
       "  'early',\n",
       "  'period']]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_sents[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "lower_bigram = Phraser(Phrases(lower_sents))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'two', b'daughters'): (19, 11.080802900992637),\n",
       " (b'her', b'sister'): (201, 16.93971298099339),\n",
       " (b'very', b'early'): (25, 10.516998773665177),\n",
       " (b'her', b'mother'): (253, 10.70812618607742),\n",
       " (b'long', b'ago'): (38, 59.226442015336005),\n",
       " (b'more', b'than'): (562, 28.529926612065935),\n",
       " (b'had', b'been'): (1260, 21.583193129694834),\n",
       " (b'an', b'excellent'): (58, 37.41859680854167),\n",
       " (b'sixteen', b'years'): (15, 131.42913000977515),\n",
       " (b'miss', b'taylor'): (48, 420.4340982546865),\n",
       " (b'mr', b'woodhouse'): (132, 104.19907841850323),\n",
       " (b'very', b'fond'): (30, 24.185726346489627),\n",
       " (b'passed', b'away'): (25, 11.751473221742694),\n",
       " (b'too', b'much'): (177, 30.36309017383541),\n",
       " (b'did', b'not'): (977, 10.846196223896685),\n",
       " (b'any', b'means'): (28, 14.294148100212627),\n",
       " (b'after', b'dinner'): (22, 18.60737125272944),\n",
       " (b'mr', b'weston'): (162, 91.63290824201266),\n",
       " (b'five', b'years'): (42, 37.66428596665674),\n",
       " (b'years', b'old'): (176, 48.599094446190286),\n",
       " (b'seven', b'years'): (53, 50.3345604292756),\n",
       " (b'each', b'other'): (239, 71.31277029783762),\n",
       " (b'well', b'informed'): (8, 14.185028016786625),\n",
       " (b'a', b'mile'): (49, 11.700110753652233),\n",
       " (b'difference', b'between'): (44, 207.86784241868986),\n",
       " (b'mrs', b'weston'): (249, 180.6778969011602),\n",
       " (b'could', b'not'): (1059, 10.213333164207079),\n",
       " (b'having', b'been'): (49, 10.723750443105281),\n",
       " (b'sixteen', b'miles'): (6, 105.040625),\n",
       " (b'miles', b'off'): (16, 32.99182066941624),\n",
       " (b'at', b'hartfield'): (67, 25.555992478744276),\n",
       " (b'her', b'husband'): (168, 26.67842743680748),\n",
       " (b'in', b'spite'): (105, 13.346436370855669),\n",
       " (b'emma', b'could'): (61, 10.88608805283633),\n",
       " (b'every', b'body'): (148, 39.26110856993498),\n",
       " (b'no', b'means'): (80, 26.766046928639682),\n",
       " (b'able', b'to'): (349, 10.854471217684639),\n",
       " (b'very', b'much'): (241, 15.43191856451234),\n",
       " (b'have', b'been'): (986, 17.20622462716941),\n",
       " (b'great', b'deal'): (182, 110.16914388000741),\n",
       " (b'agree', b'with'): (26, 13.12648342622773),\n",
       " (b'good', b'humoured'): (30, 149.07455772926625),\n",
       " (b'for', b'ever'): (565, 10.477844500702485),\n",
       " (b'three', b'times'): (41, 38.14441525690869),\n",
       " (b'my', b'dear'): (340, 26.343257103019322),\n",
       " (b'last', b'night'): (70, 23.230537949447992),\n",
       " (b'doubt', b'whether'): (12, 19.564378663784144),\n",
       " (b'anywhere', b'else'): (6, 15.30646630236794),\n",
       " (b'i', b'am'): (2445, 16.330282814272387),\n",
       " (b'very', b'glad'): (46, 16.952537612290158),\n",
       " (b'am', b'sure'): (282, 60.9206736247954),\n",
       " (b'very', b'pretty'): (40, 18.02785881936292),\n",
       " (b'be', b'able'): (121, 10.915272046078586),\n",
       " (b'immediately', b'afterwards'): (10, 37.530798337572115),\n",
       " (b'mr', b'knightley'): (277, 179.5658713081734),\n",
       " (b'sensible', b'man'): (17, 13.469145146927872),\n",
       " (b'intimate', b'friend'): (6, 20.19472630173565),\n",
       " (b'connected', b'with'): (31, 16.865113476644794),\n",
       " (b'elder', b'brother'): (6, 14.417929653989134),\n",
       " (b'than', b'usual'): (30, 27.96484669654346),\n",
       " (b'brunswick', b'square'): (11, 2374.2341399607585),\n",
       " (b'some', b'time'): (149, 11.678170286892607),\n",
       " (b'poor', b'isabella'): (11, 43.036881601877866),\n",
       " (b'am', b'afraid'): (65, 24.40430621044607),\n",
       " (b'moonlight', b'night'): (6, 13.233464566929133),\n",
       " (b'look', b'at'): (188, 10.167669372199262),\n",
       " (b'vast', b'deal'): (11, 58.66522301228184),\n",
       " (b'an', b'hour'): (155, 40.46461919025373),\n",
       " (b'pretty', b'well'): (22, 13.991375757171793),\n",
       " (b'tolerably', b'well'): (7, 13.779741502021295),\n",
       " (b'miss', b'woodhouse'): (173, 272.89637286224394),\n",
       " (b'you', b'please'): (94, 10.458014920259812),\n",
       " (b'any', b'rate'): (47, 81.39444780766237),\n",
       " (b'very', b'true'): (50, 13.110718065819091),\n",
       " (b',\"', b'said'): (2585, 35.208800203215695),\n",
       " (b'my', b'dearest'): (20, 15.989439634668441),\n",
       " (b'so', b'much'): (501, 16.689081989684137),\n",
       " (b'much', b'less'): (40, 18.956871177506912),\n",
       " (b'any', b'body'): (93, 20.81402827327549),\n",
       " (b'has', b'been'): (266, 28.01515665997839),\n",
       " (b'been', b'used'): (29, 13.60480451219398),\n",
       " (b'dear', b'emma'): (33, 26.724453867413775),\n",
       " (b'every', b'thing'): (258, 26.813583851480026),\n",
       " (b'very', b'sorry'): (34, 20.451631026452166),\n",
       " (b'turned', b'away'): (50, 18.47583754119931),\n",
       " (b'divided', b'between'): (10, 32.86799217731421),\n",
       " (b'how', b'much'): (142, 13.223145529540588),\n",
       " (b'four', b'years'): (23, 17.08789651812486),\n",
       " (b'years', b'ago'): (56, 157.92138920022722),\n",
       " (b'any', b'thing'): (384, 34.60353767883287),\n",
       " (b'oh', b'dear'): (22, 13.071010293556995),\n",
       " (b'need', b'not'): (108, 12.811033130226706),\n",
       " (b'ever', b'since'): (68, 42.54639154544724),\n",
       " (b'leave', b'off'): (19, 10.456551581109641),\n",
       " (b'match', b'making'): (6, 19.514707779641338),\n",
       " (b'young', b'lady'): (73, 46.68694722651542),\n",
       " (b'depend', b'upon'): (45, 79.94054343302217),\n",
       " (b'more', b'likely'): (16, 10.63926988816206),\n",
       " (b'have', b'done'): (272, 12.079550287766299),\n",
       " (b',\"', b'rejoined'): (6, 10.722990216928967),\n",
       " (b'mr', b'elton'): (214, 139.40875576036868),\n",
       " (b'any', b'longer'): (32, 15.647026370007673),\n",
       " (b'very', b'well'): (211, 12.391112026636758),\n",
       " (b'young', b'man'): (266, 24.28633425456424),\n",
       " (b'dine', b'with'): (23, 13.166381552143315),\n",
       " (b'much', b'better'): (40, 10.49785543468346),\n",
       " (b'i', b'dare'): (138, 13.033485583230483),\n",
       " (b'dare', b'say'): (115, 119.19759719744675),\n",
       " (b'take', b'care'): (71, 74.57127010537992),\n",
       " (b'chapter', b'ii'): (11, 279.33240997229916),\n",
       " (b'entering', b'into'): (14, 14.764128843338215),\n",
       " (b'never', b'seen'): (42, 13.026399306383945),\n",
       " (b'mrs', b'churchill'): (59, 72.70198534025822),\n",
       " (b'refrain', b'from'): (10, 13.332613486117234),\n",
       " (b'at', b'once'): (270, 18.772289267502124),\n",
       " (b'three', b'years'): (80, 36.12160535692111),\n",
       " (b'mother', b's'): (212, 10.43349082727472),\n",
       " (b'twenty', b'years'): (71, 82.70010934937123),\n",
       " (b'according', b'to'): (792, 11.428224398751397),\n",
       " (b'had', b'begun'): (25, 11.498896738107863),\n",
       " (b'passed', b'through'): (45, 29.981417521047756),\n",
       " (b'its', b'being'): (58, 15.035551583602627),\n",
       " (b'deal', b'better'): (14, 18.324491856239064),\n",
       " (b'belonging', b'to'): (36, 10.007375856554956),\n",
       " (b'mr', b'frank'): (50, 51.13385894796941),\n",
       " (b'frank', b'churchill'): (151, 1615.1350106048417),\n",
       " (b'mrs', b'perry'): (11, 23.552718142359424),\n",
       " (b'miss', b'bates'): (113, 368.52784388923357),\n",
       " (b'a', b'few'): (452, 11.993654742645493),\n",
       " (b'few', b'days'): (53, 34.43889574044208),\n",
       " (b'i', b'suppose'): (210, 11.320989637575268),\n",
       " (b'very', b'handsome'): (21, 18.293203927526704),\n",
       " (b'an', b'irresistible'): (7, 10.743649616890554),\n",
       " (b'good', b'sense'): (28, 15.484518577039912),\n",
       " (b'had', b'already'): (64, 11.161348479021472),\n",
       " (b'long', b'enough'): (39, 14.424561747959498),\n",
       " (b'at', b'randalls'): (39, 24.914802703291915),\n",
       " (b'few', b'weeks'): (19, 130.17082616179002),\n",
       " (b'no', b'longer'): (117, 37.27164862774777),\n",
       " (b'mr', b'perry'): (36, 95.9153455928979),\n",
       " (b'chapter', b'iii'): (10, 294.85087719298247),\n",
       " (b'donwell', b'abbey'): (9, 737.1720986902222),\n",
       " (b'card', b'table'): (7, 52.05489116407124),\n",
       " (b'drawing', b'room'): (49, 219.77986922924512),\n",
       " (b'thrown', b'away'): (11, 13.991597804637394),\n",
       " (b'mrs', b'goddard'): (58, 292.6791161249692),\n",
       " (b'an', b'invitation'): (13, 13.178876863385744),\n",
       " (b'mrs', b'bates'): (30, 54.6665437867962),\n",
       " (b'those', b'who'): (174, 14.383248820933867),\n",
       " (b'as', b'possible'): (81, 10.515284953239568),\n",
       " (b'young', b'ladies'): (47, 111.39207280187263),\n",
       " (b'old', b'fashioned'): (38, 181.0280072171398),\n",
       " (b'coming', b'back'): (15, 10.421002047913248),\n",
       " (b'goddard', b's'): (34, 30.051494868668044),\n",
       " (b'found', b'herself'): (27, 10.853751672615102),\n",
       " (b's', b'sake'): (143, 27.30490695465855),\n",
       " (b'much', b'pleased'): (18, 12.52905813538587),\n",
       " (b'miss', b'smith'): (58, 148.87785876781652),\n",
       " (b'harriet', b'smith'): (31, 171.76079313432186),\n",
       " (b'several', b'years'): (10, 16.071496876195333),\n",
       " (b'pretty', b'girl'): (10, 36.100742261151815),\n",
       " (b'blue', b'eyes'): (28, 33.95451351272216),\n",
       " (b'due', b'time'): (18, 19.500628497333533),\n",
       " (b'its', b'own'): (54, 10.339536241447126),\n",
       " (b'an', b'egg'): (7, 16.473596079232184),\n",
       " (b'better', b'than'): (175, 40.46903672973475),\n",
       " (b'body', b'else'): (31, 37.603287294006286),\n",
       " (b'much', b'more'): (163, 10.196735265430883),\n",
       " (b'little', b'girl'): (54, 33.82044741555345),\n",
       " (b'at', b'last'): (512, 25.084119133118794),\n",
       " (b'chapter', b'iv'): (8, 252.72932330827066),\n",
       " (b'every', b'respect'): (14, 10.88373348044036),\n",
       " (b'guided', b'by'): (14, 22.059348262898627),\n",
       " (b'different', b'sort'): (8, 13.93659398034398),\n",
       " (b'abbey', b'mill'): (11, 1868.3499742665979),\n",
       " (b'good', b'deal'): (62, 34.988675608221904),\n",
       " (b'very', b'happy'): (45, 10.609415283099846),\n",
       " (b'mrs', b'martin'): (8, 10.982447223684451),\n",
       " (b'drink', b'tea'): (7, 29.38199300699301),\n",
       " (b'large', b'enough'): (11, 10.328337316490268),\n",
       " (b'had', b'taken'): (121, 10.546895054673817),\n",
       " (b'mr', b'martin'): (37, 92.3345987295168),\n",
       " (b'three', b'miles'): (9, 15.396834283387623),\n",
       " (b'thing', b'else'): (26, 11.724101848622253),\n",
       " (b'very', b'obliging'): (14, 23.82930511612031),\n",
       " (b'on', b'purpose'): (36, 10.243903158363866),\n",
       " (b'very', b'clever'): (15, 19.348581077191703),\n",
       " (b'miss', b'nash'): (13, 312.88118939883645),\n",
       " (b'does', b'not'): (218, 11.755881647050003),\n",
       " (b'oh', b'yes'): (33, 23.31216733177377),\n",
       " (b'very', b'entertaining'): (7, 15.091893240209531),\n",
       " (b'soon', b'as'): (277, 10.47893531442171),\n",
       " (b'have', b'seen'): (204, 12.7295316573734),\n",
       " (b'on', b'horseback'): (21, 51.189475020093916),\n",
       " (b'their', b'families'): (95, 33.21807400900406),\n",
       " (b'no', b'doubt'): (125, 34.5945564760134),\n",
       " (b'very', b'respectable'): (9, 10.061262160139687),\n",
       " (b'respectable', b'young'): (8, 26.124093264248707),\n",
       " (b'very', b'odd'): (20, 23.337979237437413),\n",
       " (b'perfectly', b'right'): (12, 15.182023486901535),\n",
       " (b'six', b'years'): (23, 29.166464467922708),\n",
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       " (b'mrs', b'harville'): (24, 82.53919224555735),\n",
       " (b'fifteen', b'years'): (10, 60.35011071877431),\n",
       " (b'charles', b'hayter'): (33, 2576.962579860055),\n",
       " (b'came', b'near'): (42, 11.125204066571548),\n",
       " (b'mansion', b'house'): (8, 28.44987460815047),\n",
       " (b'two', b'hundred'): (105, 33.2713403032416),\n",
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       " (b'within', b'reach'): (7, 16.56674242216807),\n",
       " (b'turn', b'back'): (16, 10.061840177671076),\n",
       " (b'walking', b'along'): (8, 17.573893342628093),\n",
       " (b'leaning', b'against'): (13, 24.29099376700023),\n",
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       " (b'under', b'foot'): (15, 20.587370613094873),\n",
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       " (b'provoke', b'me'): (18, 15.67267568251514),\n",
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       " (b'raised', b'up'): (35, 19.639030027092765),\n",
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       " (b'could', b'scarcely'): (18, 16.706049522741466),\n",
       " (b'passed', b'along'): (11, 15.774990874485061),\n",
       " (b'leaning', b'over'): (17, 32.99075765424357),\n",
       " (b't', b'talk'): (19, 10.789205796038152),\n",
       " (b'camden', b'place'): (29, 304.8030226700252),\n",
       " (b'straight', b'forward'): (6, 11.08933284457478),\n",
       " (b'same', b'hour'): (17, 12.501907897455677),\n",
       " (b'looking', b'glasses'): (6, 21.695137693631672),\n",
       " (b'poring', b'over'): (6, 39.405627198124265),\n",
       " (b'thirty', b'feet'): (8, 11.482173582995951),\n",
       " (b'colonel', b'wallis'): (23, 919.8152027027028),\n",
       " (b'at', b'length'): (101, 22.85664635341284),\n",
       " (b'carried', b'away'): (73, 65.89981996296747),\n",
       " (b'greater', b'than'): (58, 46.92382276332348),\n",
       " (b'miss', b'carteret'): (12, 296.58529411764704),\n",
       " (b'lady', b'dalrymple'): (25, 567.8937488267317),\n",
       " (b'laura', b'place'): (7, 20.594798829055758),\n",
       " (b'be', b'established'): (41, 12.514923983865962),\n",
       " (b'mrs', b'smith'): (79, 133.20515177750607),\n",
       " (b'westgate', b'buildings'): (7, 3878.4230769230767),\n",
       " (b'at', b'liberty'): (25, 11.17812683597344),\n",
       " (b'five', b'thousand'): (31, 35.86163157834745),\n",
       " (b'whose', b'names'): (9, 17.589220303506018),\n",
       " (b'her', b'ladyship'): (22, 32.97674284395198),\n",
       " (b'ladyship', b's'): (10, 11.322082996496901),\n",
       " (b'old', b'gentleman'): (32, 24.07985483618954),\n",
       " (b'their', b'minds'): (18, 15.50176787086856),\n",
       " (b'almost', b'entirely'): (13, 33.520817751184246),\n",
       " (b'lower', b'part'): (8, 14.360893094499653),\n",
       " (b'staring', b'at'): (33, 23.08283191628515),\n",
       " (b'ay', b'ay'): (6, 102.04655085174566),\n",
       " (b'an', b'oath'): (39, 43.30687629076502),\n",
       " (b'wiser', b'than'): (8, 28.37160810303864),\n",
       " (b'prejudice', b'against'): (7, 37.30402614217892),\n",
       " (b'both', b'sides'): (31, 93.4670833729442),\n",
       " (b'my', b'soul'): (259, 16.066751210923982),\n",
       " (b'same', b'instant'): (19, 24.46954622664402),\n",
       " (b'their', b'seats'): (12, 12.91813989239047),\n",
       " (b'their', b'mouths'): (24, 24.960473690381583),\n",
       " (b'short', b'silence'): (9, 17.742932551319647),\n",
       " (b'fifty', b'pounds'): (6, 33.29484921857803),\n",
       " (b'be', b'saved'): (61, 12.820166032252938),\n",
       " (b'hard', b'hearted'): (6, 30.946447752033144),\n",
       " (b'some', b'moments'): (14, 21.24516597218971),\n",
       " (b'exclaimed', b'mrs'): (11, 11.847730944338375),\n",
       " (b'compassion', b'on'): (20, 12.135435888384333),\n",
       " (b'an', b'explanation'): (12, 15.443996324280173),\n",
       " (b'our', b'hearts'): (21, 17.06646733400796),\n",
       " (b'minutes', b'afterwards'): (7, 21.366081045290017),\n",
       " (b'make', b'haste'): (38, 69.71776454772422),\n",
       " (b'n', b't'): (19, 110.43069461827284),\n",
       " (b'rising', b'sun'): (7, 11.4529037631559),\n",
       " (b'an', b'atonement'): (66, 83.74078006943026),\n",
       " (b'atonement', b'for'): (65, 20.65632201567061),\n",
       " (b'next', b'instant'): (8, 11.76765535349606),\n",
       " (b'she', b'doted'): (7, 14.810751266798853),\n",
       " (b'god', b'forbid'): (30, 46.144377261328756),\n",
       " (b'i', b'll'): (384, 11.17502796097598),\n",
       " (b'll', b'answer'): (12, 13.013882743362831),\n",
       " (b'market', b'place'): (13, 39.58480813896431),\n",
       " (b'poured', b'out'): (53, 41.589583712234585),\n",
       " (b'at', b'norland'): (19, 17.421005219837852),\n",
       " (b'many', b'generations'): (11, 16.534145874894104),\n",
       " (b'seven', b'thousand'): (27, 31.259095392419333),\n",
       " (b'mr', b'dashwood'): (15, 10.190698520494786),\n",
       " (b'john', b'dashwood'): (37, 157.761220299208),\n",
       " (b'four', b'thousand'): (45, 51.45229768371371),\n",
       " (b'three', b'thousand'): (45, 26.103242228789615),\n",
       " (b'mrs', b'dashwood'): (121, 149.97722901761674),\n",
       " (b'miss', b'dashwoods'): (23, 254.21596638655464),\n",
       " (b'edward', b'ferrars'): (13, 135.88635597978663),\n",
       " (b'younger', b'brother'): (8, 31.67883135242683),\n",
       " (b'few', b'miles'): (7, 14.237434111445785),\n",
       " (b'replied', b'elinor'): (26, 38.56234426453405),\n",
       " (b'mrs', b'ferrars'): (73, 170.42505281471358),\n",
       " (b'barton', b'park'): (12, 511.6875679594056),\n",
       " (b'from', b'whence'): (44, 15.950059078483806),\n",
       " (b'barton', b'cottage'): (7, 104.5866897147796),\n",
       " (b'sir', b'john'): (113, 127.78658844235845),\n",
       " (b'at', b'barton'): (35, 22.230656741205607),\n",
       " (b'lady', b'middleton'): (95, 500.3819045606168),\n",
       " (b'be', b'fulfilled'): (39, 13.72604565972396),\n",
       " (b'their', b'arrival'): (15, 11.398358728579826),\n",
       " (b'present', b'case'): (12, 20.32458969190901),\n",
       " (b'mrs', b'jennings'): (229, 317.3131418135843),\n",
       " (b'colonel', b'brandon'): (132, 1667.519921875),\n",
       " (b'now', b'therefore'): (145, 11.124642048311067),\n",
       " (b'ill', b'natured'): (11, 147.80960912052115),\n",
       " (b'blue', b'sky'): (11, 51.83932141429143),\n",
       " (b'rose', b'up'): (112, 34.00644003284101),\n",
       " (b'at', b'allenham'): (8, 10.991824722040551),\n",
       " (b'miss', b'dashwood'): (70, 131.14315726290516),\n",
       " (b'cried', b'marianne'): (34, 25.0791653802614),\n",
       " (b'mr', b'willoughby'): (36, 36.686514673781225),\n",
       " (b'miss', b'marianne'): (31, 20.916503563450693),\n",
       " (b'aye', b'aye'): (36, 468.90135),\n",
       " (b'have', b'erred'): (10, 17.591061335566256),\n",
       " (b'pronounce', b'him'): (19, 17.59389669411188),\n",
       " (b'by', b'reason'): (70, 10.359210631680098),\n",
       " (b'an', b'everlasting'): (37, 33.79199195739935),\n",
       " (b'seven', b'days'): (103, 82.77954431228012),\n",
       " (b'by', b'accident'): (20, 16.659403636043233),\n",
       " (b'went', b'out'): (262, 11.679230644951586),\n",
       " (b'won', b't'): (219, 217.3954908123791),\n",
       " (b'miss', b'williams'): (6, 72.63313325330132),\n",
       " (b'laughed', b'heartily'): (6, 104.9677307425399),\n",
       " (b'considerable', b'time'): (10, 11.403428752365373),\n",
       " (b'two', b'sides'): (13, 12.986418686513664),\n",
       " (b'at', b'delaford'): (11, 13.19018966644866),\n",
       " (b'two', b'thousand'): (76, 23.96682269843838),\n",
       " (b'seven', b'hundred'): (50, 63.02087384034221),\n",
       " (b'can', b'possibly'): (10, 14.130761757067319),\n",
       " (b'burst', b'into'): (18, 13.516455983337801),\n",
       " (b'turning', b'round'): (15, 21.605116375400833),\n",
       " (b'mr', b'ferrars'): (26, 41.483981977275704),\n",
       " (b'combe', b'magna'): (11, 18907.3125),\n",
       " (b'mrs', b'palmer'): (37, 135.40263936386714),\n",
       " (b'mr', b'palmer'): (35, 100.05413092849427),\n",
       " (b'without', b'ceasing'): (8, 82.0051504472757),\n",
       " (b'stared', b'at'): (14, 13.489966704322493),\n",
       " (b't', b'think'): (70, 10.296676867200363),\n",
       " (b'miss', b'steeles'): (29, 406.7455462184874),\n",
       " (b'most', b'beautiful'): (16, 16.30563694985349),\n",
       " (b'human', b'beings'): (7, 191.52706552706556),\n",
       " (b'sugar', b'plums'): (24, 5662.879802955666),\n",
       " (b'two', b'boys'): (13, 13.239400868718477),\n",
       " (b'miss', b'steele'): (27, 243.16309828279137),\n",
       " (b'lucy', b'steele'): (10, 285.9328922495274),\n",
       " (b'i', b'm'): (438, 16.271042011107397),\n",
       " (b'm', b'sure'): (88, 102.49120766084593),\n",
       " (b'robert', b'ferrars'): (7, 95.96098334655036),\n",
       " (b'mr', b'pratt'): (8, 85.6018675721562),\n",
       " (b'at', b'longstaple'): (7, 16.48773708306082),\n",
       " (b'poor', b'edward'): (10, 12.172840599071293),\n",
       " (b'their', b'names'): (36, 14.302226309432303),\n",
       " (b'latter', b'end'): (12, 42.203822544642854),\n",
       " (b'i', b've'): (218, 13.517866465271059),\n",
       " (b'lifted', b'up'): (151, 72.07416702839072),\n",
       " (b'third', b'day'): (65, 33.7914061089195),\n",
       " (b'starting', b'up'): (9, 11.47168738090498),\n",
       " (b't', b'know'): (147, 12.457577307748522),\n",
       " (b'returned', b'home'): (11, 12.90725432262056),\n",
       " (b'berkeley', b'street'): (16, 1449.9725490196079),\n",
       " (b'conduit', b'street'): (6, 203.71515151515152),\n",
       " (b'lit', b'up'): (23, 36.13581524985069),\n",
       " (b'as', b'follows'): (17, 14.278650094398992),\n",
       " (b'having', b'received'): (10, 11.384803552611771),\n",
       " (b'who', b'cares'): (8, 12.52589229028073),\n",
       " (b'miss', b'grey'): (10, 10.25064380590946),\n",
       " (b'fifty', b'thousand'): (11, 20.37380177348749),\n",
       " (b'why', b'don'): (28, 12.795415425355841),\n",
       " (b'thousand', b'times'): (12, 12.06362743003632),\n",
       " (b'walked', b'across'): (7, 13.91218569999655),\n",
       " (b'fourteen', b'years'): (6, 15.563975922210217),\n",
       " (b'your', b'sakes'): (16, 32.49059753954306),\n",
       " (b'bartlett', b's'): (6, 10.18987469684721),\n",
       " (b'dressing', b'gown'): (6, 509.2878787878788),\n",
       " (b'wild', b'beasts'): (16, 105.2399430740038),\n",
       " (b'miss', b'morton'): (15, 267.5957540911101),\n",
       " (b'six', b'hundred'): (66, 132.00427053900353),\n",
       " (b'harley', b'street'): (16, 1540.5958333333335),\n",
       " (b'most', b'high'): (60, 22.2500544936901),\n",
       " (b'filled', b'with'): (114, 14.087588281459942),\n",
       " (b'two', b'thirds'): (6, 42.47641112047178),\n",
       " (b'public', b'school'): (6, 43.038412291933426),\n",
       " (b\",'\", b'says'): (13, 42.67564803385647),\n",
       " (b'fell', b'upon'): (62, 13.94880910923142),\n",
       " (b's', b'office'): (29, 12.330604675176458),\n",
       " (b'yes', b'ma'): (9, 15.105834768931166),\n",
       " (b'come', b'near'): (47, 11.571024613341859),\n",
       " (b'give', b'ear'): (30, 35.78134979774324),\n",
       " (b'reminds', b'me'): (7, 14.199176259372688),\n",
       " (b'ten', b'guineas'): (6, 26.425314465408807),\n",
       " (b'south', b'east'): (7, 17.11383597097883),\n",
       " (b'mr', b'harris'): (10, 85.6018675721562),\n",
       " (b'quicker', b'than'): (6, 12.238732907193139),\n",
       " (b'bent', b'over'): (10, 11.258750628035504),\n",
       " (b'justified', b'by'): (17, 11.526506299532617),\n",
       " (b'from', b'thence'): (103, 27.334646896223614),\n",
       " (b'latter', b'days'): (12, 29.77529527559055),\n",
       " (b'sprung', b'up'): (13, 24.090543499900463),\n",
       " (b'or', b'later'): (13, 13.913825368307583),\n",
       " (b'living', b'creature'): (16, 82.51963993453354),\n",
       " (b'first', b'month'): (33, 25.952445658418213),\n",
       " (b'have', b'transgressed'): (20, 23.003695592663565),\n",
       " ...}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_bigram.phrasegrams # miss taylor, mr woodhouse, mr weston"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['jon', 'lives', 'in', 'new_york', 'city']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_bigram[\"jon lives in new york city\".split()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{(b'afar', b'off'): (52, 108.14220347465505),\n",
       " (b'burnt', b'offering'): (184, 297.524653753951),\n",
       " (b'burnt', b'offerings'): (86, 299.15702343127646),\n",
       " (b'buster', b'bear'): (142, 479.87410772225826),\n",
       " (b'captain', b'benwick'): (56, 241.49037086312987),\n",
       " (b'captain', b'wentworth'): (196, 529.8756608388247),\n",
       " (b'charles', b'hayter'): (33, 92.03437785214481),\n",
       " (b'chief', b'priests'): (65, 116.31947753846512),\n",
       " (b'colonel', b'brandon'): (132, 1313.0078125),\n",
       " (b'couldn', b't'): (89, 171.76138536935215),\n",
       " (b'cut', b'off'): (217, 129.60290535032792),\n",
       " (b'dare', b'say'): (115, 89.94000515807346),\n",
       " (b'de', b'grey'): (77, 603.2109624246722),\n",
       " (b'didn', b't'): (180, 220.51081560283686),\n",
       " (b'doesn', b't'): (53, 106.2634985949418),\n",
       " (b'don', b't'): (830, 250.30957446808512),\n",
       " (b'dr', b'bull'): (65, 680.7870294599019),\n",
       " (b'dr', b'middleton'): (40, 162.73103819257668),\n",
       " (b'drawing', b'room'): (49, 84.91494947493561),\n",
       " (b'farmer', b'brown'): (100, 386.05179596892236),\n",
       " (b'father', b'brown'): (207, 91.68277248710235),\n",
       " (b'few', b'minutes'): (86, 204.16834974753786),\n",
       " (b'few', b'moments'): (43, 107.77584531675087),\n",
       " (b'fig', b'tree'): (37, 121.73722334004026),\n",
       " (b'fine', b'flour'): (36, 86.07682458386685),\n",
       " (b'fir', b'tree'): (36, 72.6789393074867),\n",
       " (b'forty', b'years'): (68, 90.60220877269607),\n",
       " (b'frank', b'churchill'): (151, 1316.4456593286038),\n",
       " (b'gathered', b'together'): (84, 103.28066074898891),\n",
       " (b'good', b'natured'): (66, 88.69936184891343),\n",
       " (b'great', b'deal'): (182, 93.36368125424357),\n",
       " (b'green', b'forest'): (66, 336.37733627667404),\n",
       " (b'guinea', b'hen'): (51, 905.8822695035461),\n",
       " (b'high', b'places'): (99, 129.8123390846559),\n",
       " (b'holy', b'ghost'): (90, 313.0305073859987),\n",
       " (b'isn', b't'): (63, 131.96593211752787),\n",
       " (b'jane', b'fairfax'): (111, 654.5565917587609),\n",
       " (b'jesus', b'christ'): (199, 172.16816954974848),\n",
       " (b'joe', b'otter'): (47, 1271.6141235813368),\n",
       " (b'john', b'knightley'): (58, 83.03755747111268),\n",
       " (b'lady', b'middleton'): (95, 350.26733319243175),\n",
       " (b'lady', b'russell'): (147, 613.6301581282135),\n",
       " (b'little', b'jackal'): (61, 69.81254128038833),\n",
       " (b'little', b'joe'): (111, 133.28784038147822),\n",
       " (b'm', b'sure'): (88, 69.15069432539002),\n",
       " (b'ma', b'am'): (216, 157.25846601094193),\n",
       " (b'mast', b'heads'): (37, 77.7358926919519),\n",
       " (b'meat', b'offering'): (122, 210.66724956379437),\n",
       " (b'mercy', b'endureth'): (41, 269.07674062361025),\n",
       " (b'miss', b'bates'): (113, 276.39588291692513),\n",
       " (b'miss', b'dashwood'): (70, 76.66830732292917),\n",
       " (b'miss', b'fairfax'): (125, 196.19987447261062),\n",
       " (b'miss', b'smith'): (58, 73.03442128232508),\n",
       " (b'miss', b'somers'): (49, 160.06190476190477),\n",
       " (b'miss', b'taylor'): (48, 156.44059469941823),\n",
       " (b'miss', b'woodhouse'): (173, 229.03802722366902),\n",
       " (b'moby', b'dick'): (84, 4115.877551020409),\n",
       " (b'mock', b'turtle'): (56, 2528.877742946708),\n",
       " (b'mr', b'elliot'): (174, 126.18129960463163),\n",
       " (b'mr', b'elton'): (214, 121.3990121932397),\n",
       " (b'mr', b'gresham'): (49, 87.31390492359931),\n",
       " (b'mr', b'knightley'): (277, 161.74131790625913),\n",
       " (b'mr', b'weston'): (162, 75.87438262077481),\n",
       " (b'mr', b'woodhouse'): (132, 82.04651843976633),\n",
       " (b'mrs', b'clay'): (66, 93.08931456265867),\n",
       " (b'mrs', b'dashwood'): (121, 115.06873605661974),\n",
       " (b'mrs', b'elton'): (142, 93.08931456265867),\n",
       " (b'mrs', b'ferrars'): (73, 102.75628184416554),\n",
       " (b'mrs', b'goddard'): (58, 143.57843432545658),\n",
       " (b'mrs', b'jennings'): (229, 279.0655756128398),\n",
       " (b'mrs', b'musgrove'): (66, 85.21252640735679),\n",
       " (b'mrs', b'smith'): (79, 84.60327207490248),\n",
       " (b'mrs', b'theresa'): (67, 170.20061244665206),\n",
       " (b'mrs', b'weston'): (249, 160.68485093258923),\n",
       " (b'o', b'clock'): (67, 89.14789088153573),\n",
       " (b'o', b'er'): (82, 108.14993564993564),\n",
       " (b'peace', b'offerings'): (83, 176.2577199456205),\n",
       " (b'sent', b'messengers'): (43, 79.21555418015616),\n",
       " (b'sin', b'offering'): (118, 129.96079665512747),\n",
       " (b'sir', b'arthur'): (71, 131.41924812030075),\n",
       " (b'sir', b'john'): (113, 95.83994133176884),\n",
       " (b'sir', b'walter'): (136, 399.5145142857143),\n",
       " (b'six', b'hundred'): (66, 73.57615079223149),\n",
       " (b'sperm', b'whale'): (183, 297.3672297627184),\n",
       " (b'sweet', b'savour'): (43, 286.17879256965944),\n",
       " (b'take', b'heed'): (58, 86.38454061712328),\n",
       " (b'ten', b'thousand'): (82, 84.00099962514057),\n",
       " (b'thou', b'shalt'): (1282, 66.88233182614454),\n",
       " (b'thousand', b'pounds'): (48, 166.51834523092802),\n",
       " (b'thus', b'saith'): (444, 144.0289127889979),\n",
       " (b'unleavened', b'bread'): (43, 237.70041787206688),\n",
       " (b'wasn', b't'): (58, 120.2225788701394),\n",
       " (b'wee', b'l'): (35, 450.39751861042186),\n",
       " (b'without', b'blemish'): (46, 83.71359108159393),\n",
       " (b'won', b't'): (219, 189.96708776595744),\n",
       " (b'wouldn', b't'): (58, 120.2225788701394),\n",
       " (b'years', b'ago'): (56, 74.31594785893046)}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lower_bigram = Phraser(Phrases(lower_sents, min_count=32, threshold=64))\n",
    "lower_bigram.phrasegrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# as in Maas et al. (2001):\n",
    "# - leave in stop words (\"indicative of sentiment\")\n",
    "# - no stemming (\"model learns similar representations of words of the same stem when data suggests it\")\n",
    "clean_sents = []\n",
    "for s in lower_sents:\n",
    "    clean_sents.append(lower_bigram[s])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['emma', 'by', 'jane', 'austen', '1816'],\n",
       " ['volume', 'i'],\n",
       " ['chapter', 'i'],\n",
       " ['emma',\n",
       "  'woodhouse',\n",
       "  'handsome',\n",
       "  'clever',\n",
       "  'and',\n",
       "  'rich',\n",
       "  'with',\n",
       "  'a',\n",
       "  'comfortable',\n",
       "  'home',\n",
       "  'and',\n",
       "  'happy',\n",
       "  'disposition',\n",
       "  'seemed',\n",
       "  'to',\n",
       "  'unite',\n",
       "  'some',\n",
       "  'of',\n",
       "  'the',\n",
       "  'best',\n",
       "  'blessings',\n",
       "  'of',\n",
       "  'existence',\n",
       "  'and',\n",
       "  'had',\n",
       "  'lived',\n",
       "  'nearly',\n",
       "  'twenty',\n",
       "  'one',\n",
       "  'years',\n",
       "  'in',\n",
       "  'the',\n",
       "  'world',\n",
       "  'with',\n",
       "  'very',\n",
       "  'little',\n",
       "  'to',\n",
       "  'distress',\n",
       "  'or',\n",
       "  'vex',\n",
       "  'her'],\n",
       " ['she',\n",
       "  'was',\n",
       "  'the',\n",
       "  'youngest',\n",
       "  'of',\n",
       "  'the',\n",
       "  'two',\n",
       "  'daughters',\n",
       "  'of',\n",
       "  'a',\n",
       "  'most',\n",
       "  'affectionate',\n",
       "  'indulgent',\n",
       "  'father',\n",
       "  'and',\n",
       "  'had',\n",
       "  'in',\n",
       "  'consequence',\n",
       "  'of',\n",
       "  'her',\n",
       "  'sister',\n",
       "  's',\n",
       "  'marriage',\n",
       "  'been',\n",
       "  'mistress',\n",
       "  'of',\n",
       "  'his',\n",
       "  'house',\n",
       "  'from',\n",
       "  'a',\n",
       "  'very',\n",
       "  'early',\n",
       "  'period'],\n",
       " ['her',\n",
       "  'mother',\n",
       "  'had',\n",
       "  'died',\n",
       "  'too',\n",
       "  'long',\n",
       "  'ago',\n",
       "  'for',\n",
       "  'her',\n",
       "  'to',\n",
       "  'have',\n",
       "  'more',\n",
       "  'than',\n",
       "  'an',\n",
       "  'indistinct',\n",
       "  'remembrance',\n",
       "  'of',\n",
       "  'her',\n",
       "  'caresses',\n",
       "  'and',\n",
       "  'her',\n",
       "  'place',\n",
       "  'had',\n",
       "  'been',\n",
       "  'supplied',\n",
       "  'by',\n",
       "  'an',\n",
       "  'excellent',\n",
       "  'woman',\n",
       "  'as',\n",
       "  'governess',\n",
       "  'who',\n",
       "  'had',\n",
       "  'fallen',\n",
       "  'little',\n",
       "  'short',\n",
       "  'of',\n",
       "  'a',\n",
       "  'mother',\n",
       "  'in',\n",
       "  'affection'],\n",
       " ['sixteen',\n",
       "  'years',\n",
       "  'had',\n",
       "  'miss_taylor',\n",
       "  'been',\n",
       "  'in',\n",
       "  'mr_woodhouse',\n",
       "  's',\n",
       "  'family',\n",
       "  'less',\n",
       "  'as',\n",
       "  'a',\n",
       "  'governess',\n",
       "  'than',\n",
       "  'a',\n",
       "  'friend',\n",
       "  'very',\n",
       "  'fond',\n",
       "  'of',\n",
       "  'both',\n",
       "  'daughters',\n",
       "  'but',\n",
       "  'particularly',\n",
       "  'of',\n",
       "  'emma'],\n",
       " ['between',\n",
       "  '_them_',\n",
       "  'it',\n",
       "  'was',\n",
       "  'more',\n",
       "  'the',\n",
       "  'intimacy',\n",
       "  'of',\n",
       "  'sisters'],\n",
       " ['even',\n",
       "  'before',\n",
       "  'miss_taylor',\n",
       "  'had',\n",
       "  'ceased',\n",
       "  'to',\n",
       "  'hold',\n",
       "  'the',\n",
       "  'nominal',\n",
       "  'office',\n",
       "  'of',\n",
       "  'governess',\n",
       "  'the',\n",
       "  'mildness',\n",
       "  'of',\n",
       "  'her',\n",
       "  'temper',\n",
       "  'had',\n",
       "  'hardly',\n",
       "  'allowed',\n",
       "  'her',\n",
       "  'to',\n",
       "  'impose',\n",
       "  'any',\n",
       "  'restraint',\n",
       "  'and',\n",
       "  'the',\n",
       "  'shadow',\n",
       "  'of',\n",
       "  'authority',\n",
       "  'being',\n",
       "  'now',\n",
       "  'long',\n",
       "  'passed',\n",
       "  'away',\n",
       "  'they',\n",
       "  'had',\n",
       "  'been',\n",
       "  'living',\n",
       "  'together',\n",
       "  'as',\n",
       "  'friend',\n",
       "  'and',\n",
       "  'friend',\n",
       "  'very',\n",
       "  'mutually',\n",
       "  'attached',\n",
       "  'and',\n",
       "  'emma',\n",
       "  'doing',\n",
       "  'just',\n",
       "  'what',\n",
       "  'she',\n",
       "  'liked',\n",
       "  'highly',\n",
       "  'esteeming',\n",
       "  'miss_taylor',\n",
       "  's',\n",
       "  'judgment',\n",
       "  'but',\n",
       "  'directed',\n",
       "  'chiefly',\n",
       "  'by',\n",
       "  'her',\n",
       "  'own']]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_sents[0:9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sixteen',\n",
       " 'years',\n",
       " 'had',\n",
       " 'miss_taylor',\n",
       " 'been',\n",
       " 'in',\n",
       " 'mr_woodhouse',\n",
       " 's',\n",
       " 'family',\n",
       " 'less',\n",
       " 'as',\n",
       " 'a',\n",
       " 'governess',\n",
       " 'than',\n",
       " 'a',\n",
       " 'friend',\n",
       " 'very',\n",
       " 'fond',\n",
       " 'of',\n",
       " 'both',\n",
       " 'daughters',\n",
       " 'but',\n",
       " 'particularly',\n",
       " 'of',\n",
       " 'emma']"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clean_sents[6] # could consider removing stop words or common words"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Run word2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# max_vocab_size can be used instead of min_count (which has increased here)\n",
    "# model = Word2Vec(sentences=clean_sents, size=64, sg=1, window=10, min_count=10, seed=42, workers=8)\n",
    "# model.save('clean_gutenberg_model.w2v')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Explore model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# skip re-training the model with the next line:  \n",
    "model = gensim.models.Word2Vec.load('clean_gutenberg_model.w2v')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10329"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(model.wv.vocab) # down from 17k in previous notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.27275795,  0.22294798, -0.27785164, -0.21537074, -0.04375846,\n",
       "        0.35075492, -0.21310569,  0.28521448,  0.18605071,  0.22906332,\n",
       "        0.3929922 ,  0.3332729 , -0.06804646, -0.36645287, -0.26969737,\n",
       "       -0.51488483,  0.02132919,  0.07797143,  0.12759572,  0.20545809,\n",
       "       -0.46009699,  0.24983054,  0.25449356, -0.64410228, -0.20215428,\n",
       "        0.1824095 , -0.23551014,  0.82762975, -0.2430227 , -0.02013004,\n",
       "       -0.88646883, -0.06863049, -0.63370681,  0.32553154,  0.02467243,\n",
       "        0.02537833,  0.13675088, -0.08868799,  0.31126702,  0.48400268,\n",
       "       -0.60338777, -0.20596088, -0.41460729, -0.47632793, -0.02355143,\n",
       "        0.56830853,  0.15640558,  0.12009691,  0.16354683,  0.66328555,\n",
       "       -0.24750067, -0.16379237,  0.00516235,  0.83655453,  0.10755659,\n",
       "        0.13685858, -0.00376199, -0.17476274, -0.35152084, -0.01025227,\n",
       "       -0.03357989,  0.33727771,  0.05614873, -0.19056796], dtype=float32)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model['ma_am']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('madam', 0.8394622802734375),\n",
       " ('mamma', 0.8382871747016907),\n",
       " ('betty', 0.8321777582168579),\n",
       " ('nancy', 0.8240376710891724),\n",
       " ('shouldn', 0.8222858905792236),\n",
       " ('m_sure', 0.8149751424789429),\n",
       " ('madman', 0.8145883083343506),\n",
       " ('bunger', 0.8138953447341919),\n",
       " ('frederick', 0.8121578693389893),\n",
       " ('indignantly', 0.8070249557495117)]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar('ma_am') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('wilkinson', 0.720096230506897),\n",
       " ('but', 0.7161370515823364),\n",
       " ('hutton', 0.7105218172073364),\n",
       " ('todhunter', 0.708503246307373),\n",
       " ('--\"', 0.6997684240341187),\n",
       " ('\"--', 0.6975828409194946),\n",
       " ('policeman', 0.697425127029419),\n",
       " ('impatiently', 0.6903563737869263),\n",
       " ('vane', 0.684941291809082),\n",
       " ('angrily', 0.6834420561790466)]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# swap woman and man\n",
    "model.most_similar(positive=['ma_am', 'man'], negative=['woman']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('mother', 0.7831815481185913),\n",
       " ('husband', 0.7511569857597351),\n",
       " ('daughter', 0.7453563213348389),\n",
       " ('wife', 0.7420299053192139),\n",
       " ('sister', 0.739268958568573),\n",
       " ('womb', 0.6849961280822754),\n",
       " ('loved', 0.6742969751358032),\n",
       " ('sarah', 0.6667004823684692),\n",
       " ('child', 0.6640843152999878),\n",
       " ('isaac', 0.6623573303222656)]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar(positive=['father', 'woman'], negative=['man']) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reduce word vector dimensionality with t-SNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tsne = TSNE(n_components=2, n_iter=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X_2d = tsne.fit_transform(model[model.wv.vocab])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coords_df = pd.DataFrame(X_2d, columns=['x','y'])\n",
    "coords_df['token'] = model.wv.vocab.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>token</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.747333</td>\n",
       "      <td>2.430868</td>\n",
       "      <td>emma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.480182</td>\n",
       "      <td>5.843261</td>\n",
       "      <td>by</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.043642</td>\n",
       "      <td>3.466430</td>\n",
       "      <td>jane</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.065098</td>\n",
       "      <td>0.612525</td>\n",
       "      <td>volume</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.750876</td>\n",
       "      <td>4.752357</td>\n",
       "      <td>i</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          x         y   token\n",
       "0  3.747333  2.430868    emma\n",
       "1 -1.480182  5.843261      by\n",
       "2  3.043642  3.466430    jane\n",
       "3  7.065098  0.612525  volume\n",
       "4  1.750876  4.752357       i"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coords_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# coords_df.to_csv('clean_gutenberg_tsne.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualise "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coords_df = pd.read_csv('clean_gutenberg_tsne.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4jydpHCLELRTTAXPnURFHJ00A/ZNSOiFjayPtypd4czGJzVvGE5towdb8p8XB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KoT8YYWMpNRU33K8tqvNOpkEOOnfDnK002LFVtYQGKXPWmHOgLzfmSVsuAEGCoZOg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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2acbc2fa20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = coords_df.plot.scatter('x', 'y', figsize=(12,12), marker='.', s=10, alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"2e68396f-bb68-47fc-9c62-40d925011882\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      var el = document.getElementById(\"2e68396f-bb68-47fc-9c62-40d925011882\");\n",
       "      el.textContent = \"BokehJS \" + Bokeh.version + \" successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    }\n",
       "    finally {\n",
       "      delete window._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"2e68396f-bb68-47fc-9c62-40d925011882\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '2e68396f-bb68-47fc-9c62-40d925011882' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.6.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.6.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"2e68396f-bb68-47fc-9c62-40d925011882\").textContent = \"BokehJS is loading...\";\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.6.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.6.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.6.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.6.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"2e68396f-bb68-47fc-9c62-40d925011882\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "subset_df = coords_df.sample(n=5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p = figure(plot_width=800, plot_height=800)\n",
    "_ = p.text(x=subset_df.x, y=subset_df.y, text=subset_df.token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
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       "  \n",
       "    var force = false;\n",
       "  \n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "  \n",
       "  \n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "  \n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
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       "        delete window._bokeh_onload_callbacks\n",
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       "      console.info(\"Bokeh: all callbacks have finished\");\n",
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       "  \n",
       "    function load_libs(js_urls, callback) {\n",
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       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
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       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"395e4dec-b3c4-49e6-929e-bb59dfc16a00\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '395e4dec-b3c4-49e6-929e-bb59dfc16a00' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "  \n",
       "    var js_urls = [];\n",
       "  \n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = 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\",\"dtype\":\"float64\",\"shape\":[5000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[5000]}}},\"id\":\"5a472bf2-d44f-4c0e-8f8c-98f7a82c44fc\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"998f96bd-c919-412b-a7e8-b1dda8c627b9\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"4d53f25e-3cdb-4feb-af85-657f30df9e23\",\"type\":\"LinearScale\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"91af062d-5b05-491f-bc70-42458dec9cca\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"5a472bf2-d44f-4c0e-8f8c-98f7a82c44fc\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"92099d72-6126-49c2-87da-48564021abd7\",\"type\":\"Text\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"8774ce19-f79c-4e89-ada4-95f525c0292d\",\"type\":\"Text\"},\"selection_glyph\":null},\"id\":\"cddd2a33-f14d-4e20-bf9c-916282ca9712\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2c55c940-876f-47c0-98b8-512327c48ca6\",\"type\":\"ToolEvents\"},{\"attributes\":{\"text_color\":{\"value\":\"black\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"92099d72-6126-49c2-87da-48564021abd7\",\"type\":\"Text\"},{\"attributes\":{\"formatter\":{\"id\":\"4ba64996-613e-450c-9212-a12a696d6a46\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"0e3e8d2a-b469-44df-a9db-6ebb614d44a0\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"5bc2fe7d-bcb1-4c76-83a2-82cf13483484\",\"type\":\"BasicTicker\"}},\"id\":\"09533d5f-3c47-48d2-86b5-0d92aa79d08d\",\"type\":\"LinearAxis\"},{\"attributes\":{\"callback\":null},\"id\":\"4cac49e0-30ad-442d-8862-ba49e0665f5b\",\"type\":\"DataRange1d\"},{\"attributes\":{\"formatter\":{\"id\":\"66effa71-f03f-4651-8019-b0d9da146ee6\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"0e3e8d2a-b469-44df-a9db-6ebb614d44a0\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"70a53790-91cf-462c-9fbb-2ebc73891da8\",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       "            var render_items = [{\"docid\":\"1c10c46b-58ba-454a-8a41-128adabc1222\",\"elementid\":\"395e4dec-b3c4-49e6-929e-bb59dfc16a00\",\"modelid\":\"0e3e8d2a-b469-44df-a9db-6ebb614d44a0\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "  \n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"395e4dec-b3c4-49e6-929e-bb59dfc16a00\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "  \n",
       "    }\n",
       "  \n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# output_file() here"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
